REVIEWS REVIEWS REVIEWS
Who needs environmental monitoring?
Gary M Lovett1*, Douglas A Burns2, Charles T Driscoll3, Jennifer C Jenkins4, Myron J Mitchell5,
Lindsey Rustad6, James B Shanley7, Gene E Likens1, and Richard Haeuber8
Environmental monitoring is often criticized as being unscientific, too expensive, and wasteful. While some
monitoring studies do suffer from these problems, there are also many highly successful long-term monitoring
programs that have provided important scientific advances and crucial information for environmental policy.
Here, we discuss the characteristics of effective monitoring programs, and contend that monitoring should be
considered a fundamental component of environmental science and policy. We urge scientists who develop
monitoring programs to plan in advance to ensure high data quality, accessibility, and cost-effectiveness, and
we urge government agencies and other funding institutions to make greater commitments to increasing the
amount and long-term stability of funding for environmental monitoring programs.
Front Ecol Environ 2007; 5(5): 253–260
W
e use monitoring data routinely in our daily lives;
we monitor the stock market, the weather, our
blood pressure, and baseball statistics. But, does monitoring have a place in environmental science? Common criticisms of environmental monitoring are (1) that it is not
really science, but merely a fishing expedition that diverts
funds from “real” science, (2) that most monitoring data
are never used, and (3) that we can’t possibly know today
what critical questions will need to be answered in the
future. Some people feel that monitoring has no place in
rigorous environmental science, and mindless monitoring
gives the discipline a bad reputation. Who needs it?
In a nutshell:
• Environmental monitoring is often criticized as being unscientific, expensive, and wasteful
• We argue that monitoring is a crucial part of environmental
science, costs very little relative to the value of the resources
it protects and the policy it informs, and has added value in
that basic environmental monitoring data can be used for
multiple purposes
• Effective monitoring programs address clear questions, use
consistent and accepted methods to produce high-quality
data, include provisions for management and accessibility of
samples and data, and integrate monitoring into research programs that foster continual examination and use of the data
• Government agencies should commit to long-term support
for valuable monitoring programs, and funders of basic ecological and environmental research should recognize that
monitoring is a fundamental part of environmental science
1
Institute of Ecosystem Studies, Millbrook, NY *(lovettg@ecostudies.org); 2US Geological Survey, Troy, NY; 3Syracuse University,
Syracuse, NY; 4University of Vermont, Burlington, VT; 5College of
Environmental Science and Forestry, State University of New York,
Syracuse, NY; 6US Department of Agriculture Forest Service,
Cumberland, ME; 7US Geological Survey, Montpelier, VT; 8US
Environmental Protection Agency, Washington, DC
© The Ecological Society of America
In this paper, we evaluate these common perceptions of
environmental monitoring and discuss the characteristics
of successful and unsuccessful monitoring programs. We
define environmental monitoring as a time series of measurements of physical, chemical, and/or biological variables, designed to answer questions about environmental
change. These measurements may be taken at one or
multiple locations. The meaning of “long term” depends
on the time scale of the ecological process of interest, but
in this paper we focus on datasets that span decades. Our
discussion is particularly relevant, given the budgetary
constraints on current monitoring and the ongoing
debate regarding the opportunities, limitations, and costs
associated with the establishment of national environmental observatories in the US, for example the National
Ecological Observatory Network (NAS 2004), the
Hydrologic Observatories, and the Cooperative Largescale Engineering Analysis Network for Environmental
Research (NRC 2006).
Is monitoring science?
Good science involves more than just devising clever
experiments to test a specific hypothesis. Carpenter
(1998) suggests that ecosystem science is like a table supported by the four legs of theory, experimentation, crosssite comparisons, and long-term studies. Many ecosystems require long-term study because they change slowly,
and sustained monitoring of key variables provides the
principal record of change. Long-term monitoring data
also provide context for short-term experiments and
observations. For example, suppose an elegant irrigation
experiment is conducted to determine the effect of water
availability on plant production, and no response is
observed. If long-term measurements of precipitation
indicate that the experiment occurred during the wettest
year on record, the monitoring data provide important
information for interpreting these unexpected experiwww.frontiersinecology.org
253
GM Lovett et al.
Environmental monitoring
mented, they also add little to scientific understanding. The keys to good science are similar for
all forms of scientific inquiry, including monitoring: good questions, appropriate research designs,
high-quality data, and careful interpretation of the
results.
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Courtesy of EPA Clean Air Markets Division
Is monitoring cost-effective?
Monitoring not only provides the basis for formulation of science-based environmental policy, but
continued monitoring also permits evaluation of
whether the policy has had its intended effect and
has been cost-effective. Solutions to many environmental problems are expensive and technically
challenging, but the cost of monitoring programs is
generally much less than either the cost of policy
implementation or the monetary benefits associated with environmental improvement. The costeffectiveness of monitoring in implementing environmental policy is illustrated below by three
examples of major environmental issues and their
Figure 1. The National Atmospheric Deposition Program (NADP) and related monitoring efforts.
Clean Air Status and Trends Network (CASTNET) site at Prince
Edward, VA. These two atmospheric monitoring networks are crucial for Clean Water Act
quantifying atmospheric deposition and tracking responses to air-pollution
legislation. The two tall towers and the instrument shed at the left of the The Clean Water Act (CWA) of 1972, along with
photo hold the instrumentation for the air chemistry and dry deposition subsequent amendments, has established the modmeasurements made by CASTNET, and the automatic precipitation ern framework for regulating water pollution in the
collector at the right of the photo is used by the NADP for measuring rivers, lakes, wetlands, and coastal waters of the
precipitation chemistry.
US. The CWA regulates discharge from municipal
wastewater treatment plants and industrial facilimental results. Monitoring data are also necessary for ties, non-point source pollution from agricultural actividetermining whether an event is unusual or extreme and ties, wetlands protection, and many other activities. The
are useful for the development of appropriate experimen- cost of water-quality monitoring under the CWA is diffital designs. For example, long-term monitoring of atmos- cult to estimate because of the diffuse responsibilities of
pheric ozone provides the critical information on average federal, state, and local agencies under various sections of
and extreme ozone concentrations that is needed to this complex law. Accordingly, estimates of the total costs
design an appropriate experiment examining the effects of complying with the CWA vary widely, from $14.1 bilof ozone on plants. Monitoring data also contribute sig- lion per year (in 1997 dollars; Van Houtven et al. 2000)
nificantly to the parameterization and testing of environ- to as high as $93.1 billion per year (in 2001 dollars;
mental models, such as the general circulation models Johnson 2004). Judging the effectiveness of these expen(GCMs) that predict future climate change. Clearly, ditures in improving water quality has been contentious
(Smith et al. 1987; Knopman and Smith 1993), due in
monitoring is a crucial part of environmental science.
Proposals that include monitoring generally do not fare part to concerns about the quality, statistical representawell in competition for basic science funding from com- tiveness, and comparability across states of long-term
petitive grant agencies, such as the US National Science water quality measurements, which are largely the
Foundation. Reviewers often object on the grounds that responsibility of individual states (Adler et al. 1993; GAO
monitoring does not address a hypothesis, or that the 2000; Hirsch et al. 2006). A recent estimate of governhypothesis is trivial. However, careful, structured obser- ment expenses for regulation and monitoring under the
vation is as fundamental to science as is hypothesis test- CWA puts the cost at $982 million in 2001, of which
ing. Good, long-term monitoring records are rare and much less than half is likely to be attributable to waterpollution monitoring (Johnson 2004). If as much as oneextremely valuable.
Haphazard monitoring, of course, adds little to scien- third (probably an overestimate) of these expenses are for
tific knowledge. However, this also applies to other forms actual water-quality monitoring, then this value repreof scientific endeavor; when theory, experiments, or sents only 0.4–2.1% of the estimated cost of complying
cross-site comparisons are poorly designed or imple- with the CWA.
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© The Ecological Society of America
GM Lovett et al.
Environmental monitoring
Acid deposition
255
Acid deposition has been an important scientific and policy issue in North America
since the 1970s. Major policy action was
taken in the 1990 amendments to the
Clean Air Act, in which Title IV is focused
on protecting ecosystems from acidifying
deposition of sulfur and nitrogen. Title IV
has resulted in major reductions in emissions of sulfur dioxide (SO2) and nitrogen
oxides (NOx) by electric power generation
plants. By 2005, Title IV emission reduction programs had diminished annual SO2
emissions by more than seven million tons
from 1980 levels, and had reduced annual
NOx emissions by over three million tons
from 1990 levels. The most recent analysis
of the benefits and costs of compliance with
Title IV estimated the program’s benefits at Figure 2. US Department of Agriculture Forest Service technicians measure
$122 billion annually in 2010, when the decaying wood in the Delaware River Basin as part of the Forest Inventory and
program will be fully implemented, while Analysis (FIA) program. The FIA program monitors forest health and
projecting the annual cost to industry of productivity throughout the US (www.fia.fs.fed.us/).
compliance at approximately $3 billion (in
2000 dollars; Chestnut and Mills 2005). Changes in acid and, in addition, may be of future economic importance if
deposition resulting from Title IV are primarily moni- the US adopts a carbon-trading program that includes
tored by two networks (Figure 1): the National credits for carbon sequestration. The potential for US
Atmospheric Deposition Program (NADP), which mea- forests to sequester atmospheric CO2 has been estimated
sures precipitation chemistry in the US at a cost of from the data collected by the US Department of
approximately $6 million annually (V Bowersox pers Agriculture Forest Service's Forest Inventory and
comm), and by the Clean Air Status and Trends Network Analysis (FIA) program (Birdsey 1992; Birdsey and Lewis
(CASTNET), which measures ozone and dry deposition 2003; Figure 2). The primary goal of the FIA program is
at a cost of approximately $3.9 million annually. In addi- to monitor the extent, condition, productivity, uses,
tion to these air-quality monitoring programs, the US impacts of management, and health of forest ecosystems
Environmental Protection Agency (EPA) has two sur- in the US, but the FIA data are used by many researchers
face-water monitoring programs to assess the response of for a wide variety of purposes, including estimation of foracid-sensitive watersheds to changes in atmospheric est carbon sequestration. Using FIA data and other infordeposition (Stoddard et al. 2003); they are the mation, Goodale et al. (2002) estimated that the annual
Temporally Integrated Monitoring of Ecosystems (TIME) accumulation of carbon in forest ecosystems in the US
and the Long-Term Monitoring (LTM) program, which from 1990–1991 was 0.28 Pg, or 280 million tons. The
differ in intensity of sampling and selection of sampled monetary value of this ecosystem service is difficult to
lakes and streams. The TIME/LTM program currently quantify. However, recent analyses of energy policy
focuses on the areas most impacted by acid deposition: options suggest that if a carbon-trading program were
lakes in the Adirondack Mountain region of New York implemented in the US, carbon credits could be priced at
and New England and streams in the Northern $5 to $25 per ton (National Commission on Energy
Appalachian Plateau and Blue Ridge region of Virginia Policy 2004, 2005), yielding a value for forest carbon
and West Virginia. The scope and budget of this program sequestration of between $1.4 billion and $7 billion per
has been markedly reduced, from $2 million annually in year. The federal appropriation for FIA in 2003 was $59.7
the early 1990s to substantially less than $1 million today. million, supplemented by $10.2 million from other partTaken together, the total cost of these critical atmos- ners (USDA Forest Service 2004). Thus, depending on
pheric deposition and surface-water monitoring programs the price chosen for carbon credits, the cost of implerepresents less than 0.4% of the implementation costs of menting the FIA program ranges from < 1% to 5% of the
Title IV and less than 0.01% of the estimated benefits.
potential value of annual carbon sequestration in forest
ecosystems in the US. This analysis is for carbon sequestration alone, and does not consider the many other
Carbon sequestration
important uses of FIA data, such as evaluation of forest
The potential for vegetation in the US to sequester car- health and timber stocks.
bon is important for the analysis of global carbon budgets
The above examples show clearly that while large-scale
© The Ecological Society of America
www.frontiersinecology.org
Environmental monitoring
256
390
380
CO2 (ppmv)
370
360
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GM Lovett et al.
tion work, the small fraction spent on monitoring actually provides an opportunity to learn which restoration
methods work and which do not.
Are monitoring data used effectively?
340
We all know of monitoring data that have accumulated in
file cabinets (or on hard drives) and gathered dust. These
320
data may be either inaccessible to all but a few, too poor in
310
quality or too poorly documented to be useful, or they may
300
have been collected solely to fulfill a legal requirement,
Jan 58 Jan 62 Jan 66 Jan 70 Jan 74 Jan 78 Jan 82 Jan 86 Jan 90 Jan 94 Jan 98 Jan02
with no real motivation for thorough analysis and interpreFigure 3. Mean monthly atmospheric concentrations of CO2 tation. At the other end of the spectrum are datasets from
measured at Mauna Loa, HI, by CD Keeling and colleagues both individual investigators and large institutional profrom 1958 to 2004. Plotted from data available at the Carbon grams that have enormous value to environmental science
Dioxide Information Analysis Center (www.cdiac.ornl.gov).
and policy. Consider, for example, Charles David Keeling’s
record of atmospheric CO2 concentrations at Mauna Loa,
monitoring programs often require considerable expendi- Hawaii. Although Tyndall and Arrhenius proposed in the
tures, in many cases these costs are miniscule compared late 19th century that changes in atmospheric CO2 conto the value of the resources monitored and the policies centrations could affect the heat budget and surface temthat affect these resources. Furthermore, the absence of perature of Earth, the concept of global climate change
monitoring can greatly hinder evaluation of the effective- and its linkage with anthropogenic emissions of CO2 did
ness of environmental policies and programs. One exam- not emerge until Keeling began long-term measurements
ple is the lack of a uniform and integrated surface-water of atmospheric CO2 at Mauna Loa in the 1950s (Figure 3).
monitoring program to assess the Clean Water Act, as Now, global climate change is arguably the foremost issue
discussed above. Another is the inability to assess the in environmental science and policy.
Consider also measurement of the chemistry of bulk preeffectiveness of the $14–15 billion spent on river restoration projects in the US since 1990, because these projects cipitation and streamwater at the Hubbard Brook
rarely include river monitoring before and after the Experimental Forest in New Hampshire (Figures 4 and 5).
restoration effort (Bernhardt et al. 2005). While it may Begun in 1963, this is the longest-running precipitation
seem that monitoring costs take funds away from restora- and streamwater chemistry record in the US and has figured prominently in the development of the watershed–ecosystem concept, analysis of watershed bio160
geochemical cycles, and evaluation of forest
Streamwater
140
harvesting policy (Bormann and Likens 1967;
120
Likens et al. 1978; Likens and Bormann 1995).
During the scientific debate that preceded the Clean
100
Air Act Amendments of 1990, the sulfate trends
80
Precipitation
(Figure 4) at Hubbard Brook were very influential in
convincing scientists and policy makers that
60
decreasing sulfur emissions would produce substan40
tial decreases in sulfur deposition and streamwater
sulfate concentrations in the northeastern US
20
(NRC 1983).
0
A good example of a valuable, broad-scale moni1960 1965 1970 1975 1980 1985 1990 1995 2000 2005
toring program is the NADP precipitation chemWater year
istry network discussed above. The NADP data are
Figure 4. Long-term record of annual volume-weighted mean sulfate widely used because of their high quality and free
concentrations in bulk precipitation and streamwater in Watershed 6 of availability on the Internet. These data have
the Hubbard Brook Experimental Forest, NH (updated from Likens et proven effective in evaluating emissions policies
al. 2002). This data record was initiated as part of a basic study of forest for sulfur and nitrogen oxides. For example, they
ecosystem function, but has also proven valuable in assessments of were used to measure the decline in atmospheric
ecosystem response to policies controlling emissions of air pollutants. nitrate and sulfate deposition following the impleMonitoring at the Hubbard Brook Experimental Forest relies on an mentation of the 1990 Clean Air Act
effective collaboration between academic scientists and the US Amendments (Lynch et al. 2000; Butler et al. 2001,
Department of Agriculture Forest Service, which monitors hydrological 2005). The NADP program also provides a powerand meteorological variables at this site.
ful example of the value of the Internet in providSulfate concentration (µeq l-1)
330
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© The Ecological Society of America
GM Lovett et al.
Environmental monitoring
ing broad-scale access to data. Prior to 1995,
when the NADP data were first made available
online, fewer than 500 people per year
received data on tape or diskette (V Bowersox
pers comm); in contrast, more than 18 000
downloads of NADP data from the Internet
have been recorded annually in recent years
(NADP 2003).
Another crucial, large-scale monitoring program is the USGS national network of stream
gauges, which provides fundamental data
nation-wide for flood prediction and estimation of water supply. The data are used for
other scientific purposes as well, including
analysis of the impacts of climate change (Lins
and Slack 1999; McCabe and Wolock 2002;
Hodgkins et al. 2003) and testing the accuracy
of models that predict future climate change
Figure 5. The V-notch weir at Watershed 6 of the Hubbard Brook
(Milly et al. 2005).
The examples above are well known, but Experimental Forest, NH. The long-term stream chemistry monitoring data
even relatively obscure datasets can be valu- shown in Figure 4 are from this stream.
able if they are accessible and of high quality,
and if the record is of sufficient length. Climate itoring data with enduring value. Good foresight involves
researchers have unearthed many long-term records that looking ahead to anticipate potentially important enviprovide information on climate change. Examples from ronmental problems of the future and selecting key meathe US include the record of dates of spring-time wild- surements that are likely to be sensitive to change.
flower blooming and bird arrivals that Aldo Leopold Understanding the system depends on choosing the most
began at his Wisconsin farm in 1936 (Bradley et al. 1999), relevant measurements among a host of possibilities in
the changing bloom dates of lilac planted at hundreds of complex systems. Some variables are important because
sites in the mid-1960s (Schwartz and Reiter 2000; Wolfe they represent critical processes (eg net primary producet al. 2005; Figure 6), and the long-term records of lake tion, nutrient budgets); others are useful because they are
ice-out dates (Likens 2000; Magnuson et al. 2000; known controllers of ecosystem function (eg precipitaHodgkins et al. 2002) and ice thickness of rivers tion amount, phosphorus concentration in lakes); still
(Huntington et al. 2003).
others are important because people care about them (eg
The criticism that monitoring data are collected and bird species diversity). Monitoring such key variables
never used is unfortunately true in some cases, but other improves the probability that a dataset will be useful for
monitoring datasets have proven extremely important. the study of future environmental issues.
Below, we offer some guidelines for maximizing the use and value of monitoring programs.
257
Can today’s monitoring programs
Good monitoring programs are designed
around good questions, but will the questions
asked today still be important decades into the
future? Unfortunately, no one knows for certain which environmental issues will emerge
and which will recede as time passes. No
doubt, some scientist of the next century, desperately in need of historical data to address
an important problem, will look back and
wonder how environmental scientists could
have failed to take some crucial measurement,
whatever it might be. However, a combina- Figure 6. The lilac variety Syringa chinensis, “red rothomagensis”, in full
tion of good foresight and understanding of bloom. Flowering dates of clones of this plant are used for monitoring
the system being monitored can produce mon- phenological trends associated with climate change throughout the US.
© The Ecological Society of America
www.frontiersinecology.org
Courtesy of M Schwartz
answer tomorrow’s questions?
GM Lovett et al.
Environmental monitoring
258
Panel 1. The seven habits of highly effective monitoring programs*
(1) Design the program around clear and compelling scientific questions. Questions are crucial because they determine the
variables measured, spatial extent of sampling, intensity and duration of the measurements, and, ultimately, the usefulness of the data.
(2) Include review, feedback, and adaptation in the design. The guiding questions may change over time, and the measurements
should be designed to accommodate such changes.The program leaders should continually ask,“Are our questions still relevant and are
the data still providing an answer?” The program should have the capacity to adapt to changing questions and incorporate changing technology without losing the continuity of its core measurements.
(3) Choose measurements carefully and with the future in mind. Not every variable can be monitored, and the core measurements selected should be important as either basic measures of system function, indicators of change, or variables of particular human
interest. If the question involves monitoring change in a statistical population, measurements should be carefully chosen to provide a statistically representative sample of that population. Measurements should be as inexpensive as possible because the cost of the program
may determine its long-term sustainability.
(4) Maintain quality and consistency of the data. The best way to ensure that data will not be used is to compromise quality or to
change measurement methods or collection sites repeatedly.The confidence of future users of the data will depend entirely on the quality assurance program implemented at the outset. Sample collections and measurements should be rigorous, repeatable, well documented, and employ accepted methods. Methods should be changed only with great caution, and any changes should be recorded and
accompanied by an extended period in which both the new and the old methods are used in parallel, to establish comparability.
(5) Plan for long-term data accessibility and sample archiving. Metadata should provide all the relevant details of collection,
analysis, and data reduction. Raw data should be stored in an accessible form to allow new summaries or analyses if necessary. Raw data,
metadata, and descriptions of procedures should be stored in multiple locations. Data collected with public funding should be made available promptly to the public. Policies of confidentiality, data ownership, and data hold-back times should be established at the outset.
Archiving of soils, sediments, plant and animal material, and water and air samples provides an invaluable opportunity for re-analysis of
these samples in the future.
(6) Continually examine, interpret, and present the monitoring data. The best way to catch errors or notice trends is for scientists and other concerned individuals to use the data rigorously and often. Adequate resources should be committed to managing data
and evaluating, interpreting, and publishing results. These are crucial components of successful monitoring programs, but planning for
them often receives low priority compared to actual data collection.
(7) Include monitoring within an integrated research program. An integrated program may include modeling, experimentation,
and cross-site comparisons. This multi-faceted approach is the best way to ensure that the data are useful and, indeed, are used.
*With apologies to Covey (1989)
Observation of trends or spatial patterns in monitoring
data often allows us to discover emerging environmental
problems and to advance environmental science in new
directions. Examples include Keeling’s measurements of
increasing atmospheric CO2 (Keeling et al. 1976; Figure 3)
and the discovery of the “ozone hole” above Antarctica by
a team of British scientists (Farman et al. 1985). Each of
these discoveries led to new research and policy efforts
that have reverberated around the globe.
Finally, scientists of the future will look back with profound gratitude if we archive samples and not just data.
Chemical measurement techniques are sure to improve,
and new problems will require analyses that have not yet
been developed. When samples of soil, plant material,
animal specimens, water, and other environmental media
are archived, the scientists of the next century will have a
treasure trove of stored information with which to answer
the burning questions of the day.
What makes a monitoring program successful?
In this paper, we have highlighted examples of environmental monitoring that have proven useful in furthering
science and policy. Yet, as we point out above, some monitoring datasets go largely unused. How can we ensure
that monitoring programs, which consume our time and
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financial resources, will be useful in the future?
There is no single best model for the structure of a
monitoring study. Effective monitoring has been done by
individuals and small groups of scientists and by large
agencies, and has occurred at individual sites, across large
regions, and even over entire continents. Like other
forms of long-term research, the most important requirement is a personal or institutional commitment to sustain
the program (Strayer et al. 1986). When the goal is to
maintain a consistent measurement regimen for decades,
there will undoubtedly be times when funding will be
lean and much effort will be required to continue the
endeavor. A successful program must be designed to survive lean times by maintaining a solid funding base, a
core set of inexpensive measurements, and a group of
individuals dedicated to collecting, interpreting, and
using the data. Beyond this personal or institutional commitment, successful monitoring programs have several
important characteristics of design and implementation,
which we summarize in Panel 1.
Conclusions and recommendations
Who needs environmental monitoring? We all do.
Scientists need monitoring as part of integrated environmental research programs. Policy makers need monitor© The Ecological Society of America
GM Lovett et al.
ing to design, implement, and evaluate effective environmental policies. The public needs monitoring to track our
nation’s natural resources. Monitoring is not second-rate
science. Rather, it is an essential component of environmental science and deserves the careful attention of scientists and greater support from government agencies and
other funding sources.
If you are a scientist managing a monitoring program,
your responsibility is to ensure that the data are of high
quality, that data and methods are broadly accessible, and
that the program is as cost-effective as possible. The
“seven habits” listed in Panel 1 provide good operating
principles for these programs. Greater commitment is
needed to examine, interpret, and apply data that are
being collected and to cooperate with other scientists in
forming monitoring networks that are designed to promote comparability of data across sites and across scales of
space and time.
If you are a policy maker, resource manager, or a program manager in a government agency or funding institution, your responsibility is to make the commitment to
maintain and expand long-term monitoring programs.
Fickleness of funding has led to the demise of many good
monitoring programs, and Herculean efforts are often
required by scientists to continue collecting data in the
face of reduction or loss of funds. Agencies such as the US
Geological Survey, the US Department of Agriculture
Forest Service, the National Oceanic and Atmospheric
Administration, and the US Environmental Protection
Agency should evaluate their monitoring programs in the
light of national needs and take steps to ensure that those
programs are not sacrificed in tight budget years. The
National Science Foundation and other agencies with
competitive grant programs need to recognize that longterm monitoring is a critical part of the infrastructure of
environmental science and that many valuable monitoring programs are funded through investigator-initiated
research proposals. Maintenance of long-term monitoring
datasets should be a highly valued feature in the review of
proposals. At a national scale, better integration of monitoring efforts is needed to make more efficient use of the
funds now being spent on monitoring by many federal
and state agencies, universities, and private companies
(CENR 1997), and more funding is required to monitor
critical environmental indices that are not currently
being measured (Heinz Center 2006).
A renewed commitment to funding environmental
monitoring, and a clear focus on doing it well, will provide an invaluable legacy for future scientists and citizens.
Acknowledgements
This paper is a project of the Northeastern Ecosystem
Research Cooperative. We thank R Skeffington for inspiration and D Sleeper for advice and encouragement on
this paper. We acknowledge the support of the US
National Science Foundation through its “Research
© The Ecological Society of America
Environmental monitoring
Coordination Networks” program (grant DEB-0342198)
and through grants DEB 0129138 and DEB 0423259.
This paper has not been subjected to EPA peer and
administrative review; therefore, the conclusions and
opinions contained here are solely of the authors, and
should not be construed to reflect the views of the EPA.
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